Identifying Manipulated Images

Identifying Manipulated Images

Neal Krawetz, who owns a computer consulting firm called Hacker Factor, presented his own image-analysis tools last month at the Black Hat 2008 conference in Washington, DC. Among his tools was one that looks for the light direction in an image. The tool focuses on an individual pixel and finds the lightest of the surrounding pixels. It assumes that light is coming from that direction, and it processes the image according to that assumption, color-coding it based on light sources. While the results are noisy, Krawetz says, they can be used to spot disparities in lighting. He says that his tool, which has not been peer-reviewed, is meant as an aid for average people who want to consider whether an image has been manipulated–for example, people curious about content that they find online.

Cynthia Baron, associate director of digital media programs at Northeastern University and author of a book on digital forensics, is familiar with both Krawetz’s and Farid’s work. She says that digital forensics is a new enough field of research that even the best tools are still some distance away from being helpful to a general user. In the meantime, she says, “it helps to be on the alert.” Baron notes that, while sophisticated users could make fraudulent images that would evade detection by the available tools, many manipulations aren’t very sophisticated. “It’s amazing to me, some of the things that make their way onto the Web and that people believe are real,” she says. “Many of the things that software can point out, you can see with the naked eye, but you don’t notice it.”

Johnson says that he sees a need for tools that a news agency, for example, could use to quickly perform a dozen basic checks on an image to look for fraud. While it might not catch all tampering, he says, such a tool would be an important step, and it could work “like an initial spam filter.” As part of developing that type of tool, he says, work needs to be done on creating better interfaces for existing tools that would make them accessible to a general audience.